Dynamic web content management system

ABSTRACT

In one embodiment, an agent executed by a device intercepts webpage code for a website sent from an application server to a client of the website. The agent identifies a portion of the webpage code as being used for webpage analytics. The agent forms modified webpage code by disabling the portion of the webpage code, based on one or more performance metrics associated with the website. The agent sends the modified webpage code to the client of the website.

TECHNICAL FIELD

The present disclosure relates generally to computer systems, and, moreparticularly, to a dynamic web content management system.

BACKGROUND

The Internet and the World Wide Web have enabled the proliferation ofweb services available for virtually all types of businesses. Coupledwith this proliferation has also been the rise of webpage analytics,which seek to capture metrics regarding website traffic. To do so, manywebpage analytics tools operate by inserting web content such as tags,scripts, and the like into the code of a webpage under scrutiny. Thiscauses a client accessing the webpage to send requests to the analyticsservice, which are then tracked by the analytics service for purposes ofcompiling reports.

While webpage analytics can offer useful information to a websiteoperator, use of webpage analytics is also not without cost. Indeed, theadditional requests sent by the client to the analytics servicenecessarily requires additional time and resources to perform, whichcould also increase the page load time of the webpage. To date, however,a “one size fits all” approach is usually taken with respect to webpageanalytics whereby the analytics tags, scrips, etc. are manually insertedinto the webpage code and always enabled.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments herein may be better understood by referring to thefollowing description in conjunction with the accompanying drawings inwhich like reference numerals indicate identically or functionallysimilar elements, of which:

FIGS. 1A-1B illustrate an example computer network;

FIG. 2 illustrates an example computing device/node;

FIG. 3 illustrates an example application intelligence platform;

FIG. 4 illustrates an example system for implementing the exampleapplication intelligence platform;

FIG. 5 illustrates an example computing system implementing thedisclosed technology;

FIGS. 6A-6B illustrate an example architecture for dynamic web contentmanagement; and

FIG. 7 illustrates an example simplified procedure for dynamic webcontent management.

DESCRIPTION OF EXAMPLE EMBODIMENTS Overview

According to one or more embodiments of the disclosure, an agentexecuted by a device intercepts webpage code for a website sent from anapplication server to a client of the website. The agent identifies aportion of the webpage code as being used for webpage analytics. Theagent forms modified webpage code by disabling the portion of thewebpage code, based on one or more performance metrics associated withthe website. The agent sends the modified webpage code to the client ofthe website.

Other embodiments are described below, and this overview is not meant tolimit the scope of the present disclosure.

Description

A computer network is a geographically distributed collection of nodesinterconnected by communication links and segments for transporting databetween end nodes, such as personal computers and workstations, or otherdevices, such as sensors, etc. Many types of networks are available,ranging from local area networks (LANs) to wide area networks (WANs).LANs typically connect the nodes over dedicated private communicationslinks located in the same general physical location, such as a buildingor campus. WANs, on the other hand, typically connect geographicallydispersed nodes over long-distance communications links, such as commoncarrier telephone lines, optical lightpaths, synchronous opticalnetworks (SONET), synchronous digital hierarchy (SDH) links, orPowerline Communications (PLC), and others. The Internet is an exampleof a WAN that connects disparate networks throughout the world,providing global communication between nodes on various networks. Othertypes of networks, such as field area networks (FANs), neighborhood areanetworks (NANs), personal area networks (PANs), enterprise networks,etc. may also make up the components of any given computer network.

The nodes typically communicate over the network by exchanging discreteframes or packets of data according to predefined protocols, such as theTransmission Control Protocol/Internet Protocol (TCP/IP). In thiscontext, a protocol consists of a set of rules defining how the nodesinteract with each other. Computer networks may be furtherinterconnected by an intermediate network node, such as a router, toextend the effective “size” of each network.

Smart object networks, such as sensor networks, in particular, are aspecific type of network having spatially distributed autonomous devicessuch as sensors, actuators, etc., that cooperatively monitor physical orenvironmental conditions at different locations, such as, e.g.,energy/power consumption, resource consumption (e.g., water/gas/etc. foradvanced metering infrastructure or “AMI” applications) temperature,pressure, vibration, sound, radiation, motion, pollutants, etc. Othertypes of smart objects include actuators, e.g., responsible for turningon/off an engine or perform any other actions. Sensor networks, a typeof smart object network, are typically shared-media networks, such aswireless or power-line communication networks. That is, in addition toone or more sensors, each sensor device (node) in a sensor network maygenerally be equipped with a radio transceiver or other communicationport, a microcontroller, and an energy source, such as a battery.Generally, size and cost constraints on smart object nodes (e.g.,sensors) result in corresponding constraints on resources such asenergy, memory, computational speed and bandwidth.

FIG. 1A is a schematic block diagram of an example computer network 100illustratively comprising nodes/devices, such as a plurality ofrouters/devices interconnected by links or networks, as shown. Forexample, customer edge (CE) routers 110 may be interconnected withprovider edge (PE) routers 120 (e.g., PE-1, PE-2, and PE-3) in order tocommunicate across a core network, such as an illustrative networkbackbone 130. For example, routers 110, 120 may be interconnected by thepublic Internet, a multiprotocol label switching (MPLS) virtual privatenetwork (VPN), or the like. Data packets 140 (e.g., traffic/messages)may be exchanged among the nodes/devices of the computer network 100over links using predefined network communication protocols such as theTransmission Control Protocol/Internet Protocol (TCP/IP), User DatagramProtocol (UDP), Asynchronous Transfer Mode (ATM) protocol, Frame Relayprotocol, or any other suitable protocol. Those skilled in the art willunderstand that any number of nodes, devices, links, etc. may be used inthe computer network, and that the view shown herein is for simplicity.

In some implementations, a router or a set of routers may be connectedto a private network (e.g., dedicated leased lines, an optical network,etc.) or a virtual private network (VPN), such as an MPLS VPN thanks toa carrier network, via one or more links exhibiting very differentnetwork and service level agreement characteristics.

FIG. 1B illustrates an example of network 100 in greater detail,according to various embodiments. As shown, network backbone 130 mayprovide connectivity between devices located in different geographicalareas and/or different types of local networks. For example, network 100may comprise local/branch networks 160, 162 that include devices/nodes10-16 and devices/nodes 18-20, respectively, as well as a datacenter/cloud environment 150 that includes servers 152-154. Notably,local networks 160-162 and data center/cloud environment 150 may belocated in different geographic locations. Servers 152-154 may include,in various embodiments, any number of suitable servers or othercloud-based resources. As would be appreciated, network 100 may includeany number of local networks, data centers, cloud environments,devices/nodes, servers, etc.

In some embodiments, the techniques herein may be applied to othernetwork topologies and configurations. For example, the techniquesherein may be applied to peering points with high-speed links, datacenters, etc. Furthermore, in various embodiments, network 100 mayinclude one or more mesh networks, such as an Internet of Thingsnetwork. Loosely, the term “Internet of Things” or “IoT” refers touniquely identifiable objects (things) and their virtual representationsin a network-based architecture. In particular, the next frontier in theevolution of the Internet is the ability to connect more than justcomputers and communications devices, but rather the ability to connect“objects” in general, such as lights, appliances, vehicles, heating,ventilating, and air-conditioning (HVAC), windows and window shades andblinds, doors, locks, etc. The “Internet of Things” thus generallyrefers to the interconnection of objects (e.g., smart objects), such assensors and actuators, over a computer network (e.g., via IP), which maybe the public Internet or a private network.

Notably, shared-media mesh networks, such as wireless networks, areoften on what is referred to as Low-Power and Lossy Networks (LLNs),which are a class of network in which both the routers and theirinterconnect are constrained: LLN routers typically operate withconstraints, e.g., processing power, memory, and/or energy (battery),and their interconnects are characterized by, illustratively, high lossrates, low data rates, and/or instability. LLNs are comprised ofanything from a few dozen to thousands or even millions of LLN routers,and support point-to-point traffic (between devices inside the LLN),point-to-multipoint traffic (from a central control point such at theroot node to a subset of devices inside the LLN), andmultipoint-to-point traffic (from devices inside the LLN towards acentral control point). Often, an IoT network is implemented with anLLN-like architecture. For example, as shown, local network 160 may bean LLN in which CE-2 operates as a root node for nodes/devices 10-16 inthe local mesh, in some embodiments.

FIG. 2 is a schematic block diagram of an example computing device(e.g., apparatus) 200 that may be used with one or more embodimentsdescribed herein, e.g., as any of the devices shown in FIGS. 1A-1Babove, and particularly as specific devices as described further below.The device may comprise one or more network interfaces 210 (e.g., wired,wireless, etc.), at least one processor 220, and a memory 240interconnected by a system bus 250, as well as a power supply 260 (e.g.,battery, plug-in, etc.).

The network interface(s) 210 contain the mechanical, electrical, andsignaling circuitry for communicating data over links coupled to thenetwork 100, e.g., providing a data connection between device 200 andthe data network, such as the Internet. The network interfaces may beconfigured to transmit and/or receive data using a variety of differentcommunication protocols. For example, interfaces 210 may include wiredtransceivers, wireless transceivers, cellular transceivers, or the like,each to allow device 200 to communicate information to and from a remotecomputing device or server over an appropriate network. The same networkinterfaces 210 also allow communities of multiple devices 200 tointerconnect among themselves, either peer-to-peer, or up and down ahierarchy. Note, further, that the nodes may have two different types ofnetwork connections via network interface(s) 210, e.g., wireless andwired/physical connections, and that the view herein is merely forillustration. Also, while network interface(s) 210 are shown separatelyfrom power supply 260, for devices using powerline communication (PLC)or Power over Ethernet (PoE), the network interface 210 may communicatethrough the power supply 260, or may be an integral component of thepower supply.

The memory 240 comprises a plurality of storage locations that areaddressable by the processor 220 and the network interfaces 210 forstoring software programs and data structures associated with theembodiments described herein. The processor 220 may comprise hardwareelements or hardware logic adapted to execute the software programs andmanipulate the data structures 245. An operating system 242, portions ofwhich are typically resident in memory 240 and executed by theprocessor, functionally organizes the device by, among other things,invoking operations in support of software processes and/or servicesexecuting on the device. These software processes and/or services maycomprise one or more functional processes 246, and on certain devices,an illustrative monitoring process 248, as described herein. Notably,functional processes 246, when executed by processor(s) 220, cause eachparticular device 200 to perform the various functions corresponding tothe particular device's purpose and general configuration. For example,a router would be configured to operate as a router, a server would beconfigured to operate as a server, an access point (or gateway) would beconfigured to operate as an access point (or gateway), a client devicewould be configured to operate as a client device, and so on.

It will be apparent to those skilled in the art that other processor andmemory types, including various computer-readable media, may be used tostore and execute program instructions pertaining to the techniquesdescribed herein. Also, while the description illustrates variousprocesses, it is expressly contemplated that various processes may beembodied as modules configured to operate in accordance with thetechniques herein (e.g., according to the functionality of a similarprocess). Further, while the processes have been shown separately, thoseskilled in the art will appreciate that processes may be routines ormodules within other processes.

Application Intelligence Platform

The embodiments herein relate to an application intelligence platformfor application performance management. In one aspect, as discussed withrespect to FIGS. 3-5 below, performance within a networking environmentmay be monitored, specifically by monitoring applications and entities(e.g., transactions, tiers, nodes, and machines) in the networkingenvironment using agents installed at individual machines at theentities. As an example, applications may be configured to run on one ormore machines (e.g., a customer will typically run one or more nodes ona machine, where an application consists of one or more tiers, and atier consists of one or more nodes). The agents collect data associatedwith the applications of interest and associated nodes and machineswhere the applications are being operated. Examples of the collecteddata may include performance data (e.g., metrics, metadata, etc.) andtopology data (e.g., indicating relationship information). Theagent-collected data may then be provided to one or more servers orcontrollers to analyze the data.

FIG. 3 is a block diagram of an example application intelligenceplatform 300 that can implement one or more aspects of the techniquesherein. The application intelligence platform is a system that monitorsand collects metrics of performance data for an application environmentbeing monitored. At the simplest structure, the application intelligenceplatform includes one or more agents 310 and one or moreservers/controllers 320. Note that while FIG. 3 shows four agents (e.g.,Agent 1 through Agent 4) communicatively linked to a single controller,the total number of agents and controllers can vary based on a number offactors including the number of applications monitored, how distributedthe application environment is, the level of monitoring desired, thelevel of user experience desired, and so on.

The controller 320 is the central processing and administration serverfor the application intelligence platform. The controller 320 serves abrowser-based user interface (UI) 330 that is the primary interface formonitoring, analyzing, and troubleshooting the monitored environment.The controller 320 can control and manage monitoring of businesstransactions (described below) distributed over application servers.Specifically, the controller 320 can receive runtime data from agents310 (and/or other coordinator devices), associate portions of businesstransaction data, communicate with agents to configure collection ofruntime data, and provide performance data and reporting through theinterface 330. The interface 330 may be viewed as a web-based interfaceviewable by a client device 340. In some implementations, a clientdevice 340 can directly communicate with controller 320 to view aninterface for monitoring data. The controller 320 can include avisualization system 350 for displaying the reports and dashboardsrelated to the disclosed technology. In some implementations, thevisualization system 350 can be implemented in a separate machine (e.g.,a server) different from the one hosting the controller 320.

Notably, in an illustrative Software as a Service (SaaS) implementation,a controller instance may be hosted remotely by a provider of theapplication intelligence platform 300. In an illustrative on-premises(On-Prem) implementation, a controller instance may be installed locallyand self-administered.

The controllers 320 receive data from different agents 310 (e.g., Agents1-4) deployed to monitor applications, databases and database servers,servers, and end user clients for the monitored environment. Any of theagents 310 can be implemented as different types of agents with specificmonitoring duties. For example, application agents may be installed oneach server that hosts applications to be monitored. Instrumenting anagent adds an application agent into the runtime process of theapplication.

Database agents, for example, may be software (e.g., a Java program)installed on a machine that has network access to the monitoreddatabases and the controller. Database agents query the monitoreddatabases in order to collect metrics and pass those metrics along fordisplay in a metric browser (e.g., for database monitoring and analysiswithin databases pages of the controller's UI 330). Multiple databaseagents can report to the same controller. Additional database agents canbe implemented as backup database agents to take over for the primarydatabase agents during a failure or planned machine downtime. Theadditional database agents can run on the same machine as the primaryagents or on different machines. A database agent can be deployed ineach distinct network of the monitored environment. Multiple databaseagents can run under different user accounts on the same machine.

Standalone machine agents, on the other hand, may be standalone programs(e.g., standalone Java programs) that collect hardware-relatedperformance statistics from the servers (or other suitable devices) inthe monitored environment. The standalone machine agents can be deployedon machines that host application servers, database servers, messagingservers, Web servers, etc. A standalone machine agent has an extensiblearchitecture (e.g., designed to accommodate changes).

End user monitoring (EUM) may be performed using browser agents andmobile agents to provide performance information from the point of viewof the client, such as a web browser or a mobile native application.Through EUM, web use, mobile use, or combinations thereof (e.g., by realusers or synthetic agents) can be monitored based on the monitoringneeds. Notably, browser agents (e.g., agents 310) can include Reportersthat report monitored data to the controller.

Monitoring through browser agents and mobile agents are generally unlikemonitoring through application agents, database agents, and standalonemachine agents that are on the server. In particular, browser agents maygenerally be embodied as small files using web-based technologies, suchas JavaScript agents injected into each instrumented web page (e.g., asclose to the top as possible) as the web page is served, and areconfigured to collect data. Once the web page has completed loading, thecollected data may be bundled into a beacon and sent to an EUMprocess/cloud for processing and made ready for retrieval by thecontroller. Browser real user monitoring (Browser RUM) provides insightsinto the performance of a web application from the point of view of areal or synthetic end user. For example, Browser RUM can determine howspecific Ajax or iframe calls are slowing down page load time and howserver performance impact end user experience in aggregate or inindividual cases.

A mobile agent, on the other hand, may be a small piece of highlyperformant code that gets added to the source of the mobile application.Mobile RUM provides information on the native mobile application (e.g.,iOS or Android applications) as the end users actually use the mobileapplication. Mobile RUM provides visibility into the functioning of themobile application itself and the mobile application's interaction withthe network used and any server-side applications with which the mobileapplication communicates.

Application Intelligence Monitoring: The disclosed technology canprovide application intelligence data by monitoring an applicationenvironment that includes various services such as web applicationsserved from an application server (e.g., Java virtual machine (JVM),Internet Information Services (IIS), Hypertext Preprocessor (PHP) Webserver, etc.), databases or other data stores, and remote services suchas message queues and caches. The services in the applicationenvironment can interact in various ways to provide a set of cohesiveuser interactions with the application, such as a set of user servicesapplicable to end user customers.

Application Intelligence Modeling: Entities in the applicationenvironment (such as the JBoss service, MQSeries modules, and databases)and the services provided by the entities (such as a login transaction,service or product search, or purchase transaction) may be mapped to anapplication intelligence model. In the application intelligence model, abusiness transaction represents a particular service provided by themonitored environment. For example, in an e-commerce application,particular real-world services can include a user logging in, searchingfor items, or adding items to the cart. In a content portal, particularreal-world services can include user requests for content such assports, business, or entertainment news. In a stock trading application,particular real-world services can include operations such as receivinga stock quote, buying, or selling stocks.

Business Transactions: A business transaction representation of theparticular service provided by the monitored environment provides a viewon performance data in the context of the various tiers that participatein processing a particular request. A business transaction, which mayeach be identified by a unique business transaction identification (ID),represents the end-to-end processing path used to fulfill a servicerequest in the monitored environment (e.g., adding items to a shoppingcart, storing information in a database, purchasing an item online,etc.). Thus, a business transaction is a type of user-initiated actionin the monitored environment defined by an entry point and a processingpath across application servers, databases, and potentially many otherinfrastructure components. Each instance of a business transaction is anexecution of that transaction in response to a particular user request(e.g., a socket call, illustratively associated with the TCP layer). Abusiness transaction can be created by detecting incoming requests at anentry point and tracking the activity associated with request at theoriginating tier and across distributed components in the applicationenvironment (e.g., associating the business transaction with a 4-tupleof a source IP address, source port, destination IP address, anddestination port). A flow map can be generated for a businesstransaction that shows the touch points for the business transaction inthe application environment. In one embodiment, a specific tag may beadded to packets by application specific agents for identifying businesstransactions (e.g., a custom header field attached to a HyperTextTransfer Protocol (HTTP) payload by an application agent, or by anetwork agent when an application makes a remote socket call), such thatpackets can be examined by network agents to identify the businesstransaction identifier (ID) (e.g., a Globally Unique Identifier (GUID)or Universally Unique Identifier (UUID)).

Performance monitoring can be oriented by business transaction to focuson the performance of the services in the application environment fromthe perspective of end users. Performance monitoring based on businesstransactions can provide information on whether a service is available(e.g., users can log in, check out, or view their data), response timesfor users, and the cause of problems when the problems occur.

A business application is the top-level container in the applicationintelligence model. A business application contains a set of relatedservices and business transactions. In some implementations, a singlebusiness application may be needed to model the environment. In someimplementations, the application intelligence model of the applicationenvironment can be divided into several business applications. Businessapplications can be organized differently based on the specifics of theapplication environment. One consideration is to organize the businessapplications in a way that reflects work teams in a particularorganization, since role-based access controls in the Controller UI areoriented by business application.

A node in the application intelligence model corresponds to a monitoredserver or JVM in the application environment. A node is the smallestunit of the modeled environment. In general, a node corresponds to anindividual application server, JVM, or Common Language Runtime (CLR) onwhich a monitoring Agent is installed. Each node identifies itself inthe application intelligence model. The Agent installed at the node isconfigured to specify the name of the node, tier, and businessapplication under which the Agent reports data to the Controller.

Business applications contain tiers, the unit in the applicationintelligence model that includes one or more nodes. Each node representsan instrumented service (such as a web application). While a node can bea distinct application in the application environment, in theapplication intelligence model, a node is a member of a tier, which,along with possibly many other tiers, make up the overall logicalbusiness application.

Tiers can be organized in the application intelligence model dependingon a mental model of the monitored application environment. For example,identical nodes can be grouped into a single tier (such as a cluster ofredundant servers). In some implementations, any set of nodes, identicalor not, can be grouped for the purpose of treating certain performancemetrics as a unit into a single tier.

The traffic in a business application flows among tiers and can bevisualized in a flow map using lines among tiers. In addition, the linesindicating the traffic flows among tiers can be annotated withperformance metrics. In the application intelligence model, there maynot be any interaction among nodes within a single tier. Also, in someimplementations, an application agent node cannot belong to more thanone tier. Similarly, a machine agent cannot belong to more than onetier. However, more than one machine agent can be installed on amachine.

A backend is a component that participates in the processing of abusiness transaction instance. A backend is not instrumented by anagent. A backend may be a web server, database, message queue, or othertype of service. The agent recognizes calls to these backend servicesfrom instrumented code (called exit calls). When a service is notinstrumented and cannot continue the transaction context of the call,the agent determines that the service is a backend component. The agentpicks up the transaction context at the response at the backend andcontinues to follow the context of the transaction from there.

Performance information is available for the backend call. For detailedtransaction analysis for the leg of a transaction processed by thebackend, the database, web service, or other application need to beinstrumented.

The application intelligence platform uses both self-learned baselinesand configurable thresholds to help identify application issues. Acomplex distributed application has a large number of performancemetrics and each metric is important in one or more contexts. In suchenvironments, it is difficult to determine the values or ranges that arenormal for a particular metric; set meaningful thresholds on which tobase and receive relevant alerts; and determine what is a “normal”metric when the application or infrastructure undergoes change. Forthese reasons, the disclosed application intelligence platform canperform anomaly detection based on dynamic baselines or thresholds.

The disclosed application intelligence platform automatically calculatesdynamic baselines for the monitored metrics, defining what is “normal”for each metric based on actual usage. The application intelligenceplatform uses these baselines to identify subsequent metrics whosevalues fall out of this normal range. Static thresholds that are tediousto set up and, in rapidly changing application environments,error-prone, are no longer needed.

The disclosed application intelligence platform can use configurablethresholds to maintain service level agreements (SLAs) and ensureoptimum performance levels for system by detecting slow, very slow, andstalled transactions. Configurable thresholds provide a flexible way toassociate the right business context with a slow request to isolate theroot cause.

In addition, health rules can be set up with conditions that use thedynamically generated baselines to trigger alerts or initiate othertypes of remedial actions when performance problems are occurring or maybe about to occur.

For example, dynamic baselines can be used to automatically establishwhat is considered normal behavior for a particular application.Policies and health rules can be used against baselines or other healthindicators for a particular application to detect and troubleshootproblems before users are affected. Health rules can be used to definemetric conditions to monitor, such as when the “average response time isfour times slower than the baseline”. The health rules can be createdand modified based on the monitored application environment.

Examples of health rules for testing business transaction performancecan include business transaction response time and business transactionerror rate. For example, health rule that tests whether the businesstransaction response time is much higher than normal can define acritical condition as the combination of an average response timegreater than the default baseline by 3 standard deviations and a loadgreater than 50 calls per minute. In some implementations, this healthrule can define a warning condition as the combination of an averageresponse time greater than the default baseline by 2 standard deviationsand a load greater than 100 calls per minute. In some implementations,the health rule that tests whether the business transaction error rateis much higher than normal can define a critical condition as thecombination of an error rate greater than the default baseline by 3standard deviations and an error rate greater than 10 errors per minuteand a load greater than 50 calls per minute. In some implementations,this health rule can define a warning condition as the combination of anerror rate greater than the default baseline by 2 standard deviationsand an error rate greater than 5 errors per minute and a load greaterthan 50 calls per minute. These are non-exhaustive and non-limitingexamples of health rules and other health rules can be defined asdesired by the user.

Policies can be configured to trigger actions when a health rule isviolated or when any event occurs. Triggered actions can includenotifications, diagnostic actions, auto-scaling capacity, runningremediation scripts.

Most of the metrics relate to the overall performance of the applicationor business transaction (e.g., load, average response time, error rate,etc.) or of the application server infrastructure (e.g., percentage CPUbusy, percentage of memory used, etc.). The Metric Browser in thecontroller UI can be used to view all of the metrics that the agentsreport to the controller.

In addition, special metrics called information points can be created toreport on how a given business (as opposed to a given application) isperforming. For example, the performance of the total revenue for acertain product or set of products can be monitored. Also, informationpoints can be used to report on how a given code is performing, forexample how many times a specific method is called and how long it istaking to execute. Moreover, extensions that use the machine agent canbe created to report user defined custom metrics. These custom metricsare base-lined and reported in the controller, just like the built-inmetrics.

All metrics can be accessed programmatically using a RepresentationalState Transfer (REST) API that returns either the JavaScript ObjectNotation (JSON) or the eXtensible Markup Language (XML) format. Also,the REST API can be used to query and manipulate the applicationenvironment.

Snapshots provide a detailed picture of a given application at a certainpoint in time. Snapshots usually include call graphs that allow thatenables drilling down to the line of code that may be causingperformance problems. The most common snapshots are transactionsnapshots.

FIG. 4 illustrates an example application intelligence platform (system)400 for performing one or more aspects of the techniques herein. Thesystem 400 in FIG. 4 includes client 405, client device 492, mobiledevice 415, network 420, network server 425, application servers 430,440, 450, and 460, asynchronous network machine 470, data stores 480 and485, controller 490, and data collection server 495. The controller 490can include visualization system 496 for providing displaying of thereport generated for performing the field name recommendations for fieldextraction as disclosed in the present disclosure. In someimplementations, the visualization system 496 can be implemented in aseparate machine (e.g., a server) different from the one hosting thecontroller 490.

Client 405 may include network browser 410 and be implemented as acomputing device, such as for example a laptop, desktop, workstation, orsome other computing device. Network browser 410 may be a clientapplication for viewing content provided by an application server, suchas application server 430 via network server 425 over network 420.

Network browser 410 may include agent 412. Agent 412 may be installed onnetwork browser 410 and/or client 405 as a network browser add-on,downloading the application to the server, or in some other manner.Agent 412 may be executed to monitor network browser 410, the operatingsystem of client 405, and any other application, API, or anothercomponent of client 405. Agent 412 may determine network browsernavigation timing metrics, access browser cookies, monitor code, andtransmit data to data collection server 495, controller 490, or anotherdevice. Agent 412 may perform other operations related to monitoring arequest or a network at client 405 as discussed herein including reportgenerating.

Mobile device 415 is connected to network 420 and may be implemented asa portable device suitable for sending and receiving content over anetwork, such as for example a mobile phone, smart phone, tabletcomputer, or other portable device. Both client 405 and mobile device415 may include hardware and/or software configured to access a webservice provided by network server 425.

Mobile device 415 may include network browser 417 and an agent 419.Mobile device may also include client applications and other code thatmay be monitored by agent 419. Agent 419 may reside in and/orcommunicate with network browser 417, as well as communicate with otherapplications, an operating system, APIs and other hardware and softwareon mobile device 415. Agent 419 may have similar functionality as thatdescribed herein for agent 412 on client 405, and may report data todata collection server 495 and/or controller 490.

Network 420 may facilitate communication of data among differentservers, devices and machines of system 400 (some connections shown withlines to network 420, some not shown). The network may be implemented asa private network, public network, intranet, the Internet, a cellularnetwork, Wi-Fi network, VoIP network, or a combination of one or more ofthese networks. The network 420 may include one or more machines such asload balance machines and other machines.

Network server 425 is connected to network 420 and may receive andprocess requests received over network 420. Network server 425 may beimplemented as one or more servers implementing a network service, andmay be implemented on the same machine as application server 430 or oneor more separate machines. When network 420 is the Internet, networkserver 425 may be implemented as a web server.

Application server 430 communicates with network server 425, applicationservers 440 and 450, and controller 490. Application server 450 may alsocommunicate with other machines and devices (not illustrated in FIG. 4). Application server 430 may host an application or portions of adistributed application. The host application 432 may be in one of manyplatforms, such as including a Java, PHP, .Net, and Node.JS, beimplemented as a Java virtual machine, or include some other host type.Application server 430 may also include one or more agents 434 (i.e.,“modules”), including a language agent, machine agent, and networkagent, and other software modules. Application server 430 may beimplemented as one server or multiple servers as illustrated in FIG. 4 .

Application 432 and other software on application server 430 may beinstrumented using byte code insertion, or byte code instrumentation(BCI), to modify the object code of the application or other software.The instrumented object code may include code used to detect callsreceived by application 432, calls sent by application 432, andcommunicate with agent 434 during execution of the application. BCI mayalso be used to monitor one or more sockets of the application and/orapplication server in order to monitor the socket and capture packetscoming over the socket.

In some embodiments, server 430 may include applications and/or codeother than a virtual machine. For example, servers 430, 440, 450, and460 may each include Java code, .Net code, PHP code, Ruby code, C code,C++ or other binary code to implement applications and process requestsreceived from a remote source. References to a virtual machine withrespect to an application server are intended to be for exemplarypurposes only.

Agents 434 on application server 430 may be installed, downloaded,embedded, or otherwise provided on application server 430. For example,agents 434 may be provided in server 430 by instrumentation of objectcode, downloading the agents to the server, or in some other manner.Agent 434 may be executed to monitor application server 430, monitorapplication 432 running in a virtual machine (or other program language,such as a PHP, .Net, or C program), machine resources, network layerdata, and communicate with byte instrumented code on application server430 and one or more applications on application server 430.

Each of agents 434, 444, 454, and 464 may include one or more agents,such as language agents, machine agents, and network agents. A languageagent may be a type of agent that is suitable to run on a particularhost. Examples of language agents include a Java agent, .Net agent, PHPagent, and other agents. The machine agent may collect data from aparticular machine on which it is installed. A network agent may capturenetwork information, such as data collected from a socket.

Agent 434 may detect operations such as receiving calls and sendingrequests by application server 430, resource usage, and incomingpackets. Agent 434 may receive data, process the data, for example byaggregating data into metrics, and transmit the data and/or metrics tocontroller 490. Agent 434 may perform other operations related tomonitoring applications and application server 430 as discussed herein.For example, agent 434 may identify other applications, share businesstransaction data, aggregate detected runtime data, and other operations.

An agent may operate to monitor a node, tier of nodes, or other entity.A node may be a software program or a hardware component (e.g., memory,processor, and so on). A tier of nodes may include a plurality of nodeswhich may process a similar business transaction, may be located on thesame server, may be associated with each other in some other way, or maynot be associated with each other.

A language agent may be an agent suitable to instrument or modify,collect data from, and reside on a host. The host may be a Java, PHP,.Net, Node.JS, or other type of platform. Language agents may collectflow data as well as data associated with the execution of a particularapplication. The language agent may instrument the lowest level of theapplication to gather the flow data. The flow data may indicate whichtier is communicating with which tier and on which port. In someinstances, the flow data collected from the language agent includes asource IP, a source port, a destination IP, and a destination port. Thelanguage agent may report the application data and call chain data to acontroller. The language agent may report the collected flow dataassociated with a particular application to a network agent.

A network agent may be a standalone agent that resides on the host andcollects network flow group data. The network flow group data mayinclude a source IP, destination port, destination IP, and protocolinformation for network flow received by an application on which networkagent is installed. The network agent may collect data by interceptingand performing packet capture on packets coming in from one or morenetwork interfaces (e.g., so that data generated/received by all theapplications using sockets can be intercepted). The network agent mayreceive flow data from a language agent that is associated withapplications to be monitored. For flows in the flow group data thatmatch flow data provided by the language agent, the network agent rollsup the flow data to determine metrics such as TCP throughput, TCP loss,latency, and bandwidth. The network agent may then report the metrics,flow group data, and call chain data to a controller. The network agentmay also make system calls at an application server to determine systeminformation, such as for example a host status check, a network statuscheck, socket status, and other information.

A machine agent, which may be referred to as an infrastructure agent,may reside on the host and collect information regarding the machinewhich implements the host. A machine agent may collect and generatemetrics from information such as processor usage, memory usage, andother hardware information.

Each of the language agent, network agent, and machine agent may reportdata to the controller. Controller 490 may be implemented as a remoteserver that communicates with agents located on one or more servers ormachines. The controller may receive metrics, call chain data and otherdata, correlate the received data as part of a distributed transaction,and report the correlated data in the context of a distributedapplication implemented by one or more monitored applications andoccurring over one or more monitored networks. The controller mayprovide reports, one or more user interfaces, and other information fora user.

Agent 434 may create a request identifier for a request received byserver 430 (for example, a request received by a client 405 or mobiledevice 415 associated with a user or another source). The requestidentifier may be sent to client 405 or mobile device 415, whicheverdevice sent the request. In embodiments, the request identifier may becreated when data is collected and analyzed for a particular businesstransaction.

Each of application servers 440, 450, and 460 may include an applicationand agents. Each application may run on the corresponding applicationserver. Each of applications 442, 452, and 462 on application servers440-460 may operate similarly to application 432 and perform at least aportion of a distributed business transaction. Agents 444, 454, and 464may monitor applications 442-462, collect and process data at runtime,and communicate with controller 490. The applications 432, 442, 452, and462 may communicate with each other as part of performing a distributedtransaction. Each application may call any application or method ofanother virtual machine.

Asynchronous network machine 470 may engage in asynchronouscommunications with one or more application servers, such as applicationserver 450 and 460. For example, application server 450 may transmitseveral calls or messages to an asynchronous network machine. Ratherthan communicate back to application server 450, the asynchronousnetwork machine may process the messages and eventually provide aresponse, such as a processed message, to application server 460.Because there is no return message from the asynchronous network machineto application server 450, the communications among them areasynchronous.

Data stores 480 and 485 may each be accessed by application servers suchas application server 460. Data store 485 may also be accessed byapplication server 450. Each of data stores 480 and 485 may store data,process data, and return queries received from an application server.Each of data stores 480 and 485 may or may not include an agent.

Controller 490 may control and manage monitoring of businesstransactions distributed over application servers 430-460. In someembodiments, controller 490 may receive application data, including dataassociated with monitoring client requests at client 405 and mobiledevice 415, from data collection server 495. In some embodiments,controller 490 may receive application monitoring data and network datafrom each of agents 412, 419, 434, 444, and 454 (also referred to hereinas “application monitoring agents”). Controller 490 may associateportions of business transaction data, communicate with agents toconfigure collection of data, and provide performance data and reportingthrough an interface. The interface may be viewed as a web-basedinterface viewable by client device 492, which may be a mobile device,client device, or any other platform for viewing an interface providedby controller 490. In some embodiments, a client device 492 may directlycommunicate with controller 490 to view an interface for monitoringdata.

Client device 492 may include any computing device, including a mobiledevice or a client computer such as a desktop, work station or othercomputing device. Client device 492 may communicate with controller 490to create and view a custom interface. In some embodiments, controller490 provides an interface for creating and viewing the custom interfaceas a content page, e.g., a web page, which may be provided to andrendered through a network browser application on client device 492.

Applications 432, 442, 452, and 462 may be any of several types ofapplications. Examples of applications that may implement applications432-462 include a Java, PHP, .Net, Node.JS, and other applications.

FIG. 5 is a block diagram of a computer system 500 for implementing thepresent technology, which is a specific implementation of device 200 ofFIG. 2 above. System 500 of FIG. 5 may be implemented in the contexts ofthe likes of client 405, client device 492, network server 425, servers430, 440, 450, 460, asynchronous network machine 470, and controller 490of FIG. 4 . (Note that the specifically configured system 500 of FIG. 5and the customized device 200 of FIG. 2 are not meant to be mutuallyexclusive, and the techniques herein may be performed by any suitablyconfigured computing device.)

The computing system 500 of FIG. 5 includes one or more processor(s) 510and memory 520. Main memory 520 stores, in part, instructions and datafor execution by processor(s) 510. Main memory 520 can store theexecutable code when in operation. The system 500 of FIG. 5 furtherincludes a mass storage device 530, portable/remote storage(s) 540,output devices 550, user input devices 560, display system(s) 570, andperipheral(s) 580.

The components shown in FIG. 5 are depicted as being connected via asingle bus 590. However, the components may be connected through one ormore data transport means. For example, processor(s) 510 and main memory520 may be connected via a local microprocessor bus, and the massstorage device 530, peripheral(s) 580, storage(s) 540, and displaysystem(s) 570 may be connected via one or more input/output (I/O) buses.

Mass storage device 530, which may be implemented with a magnetic diskdrive or an optical disk drive, is a non-volatile storage device forstoring data and instructions for use by processor(s) 510. Mass storagedevice 530 can store the system software for implementing embodiments ofthe present disclosure for purposes of loading that software into mainmemory 520.

Portable/remote storage(s) 540 may operate in conjunction with aportable non-volatile storage medium, such as a compact disk, digitalvideo disk, magnetic disk, flash storage, etc. to input and output dataand code to and from the computer system 500 of FIG. 5 . The systemsoftware for implementing embodiments of the present disclosure may bestored on such a portable medium and input to the computer system 500via the storage(s) 540.

Input devices 560 provide a portion of a user interface. Input devices560 may include an alpha-numeric keypad, such as a keyboard, forinputting alpha-numeric and other information, or a pointing device,such as a mouse, a trackball, stylus, or cursor direction keys.Additionally, the system 500 as shown in FIG. 5 includes output devices550. Examples of suitable output devices include speakers, printers,network interfaces, and monitors.

Display system(s) 570 may include a liquid crystal display (LCD) orother suitable display device. Display system(s) 570 receives textualand graphical information, and processes the information for output tothe display device.

Peripheral(s) 580 may include any type of computer support device to addadditional functionality to the computer system. For example,peripheral(s) 580 may include a modem or a router.

The components contained in the computer system 500 of FIG. 5 caninclude a personal computer, handheld computing device, telephone,mobile computing device, workstation, server, minicomputer, mainframecomputer, or any other computing device. The computer can also includedifferent bus configurations, networked platforms, multi-processorplatforms, etc. Various operating systems can be used including Unix,Linux, Windows, Apple OS, and other suitable operating systems,including mobile versions.

When implementing a mobile device such as smart phone or tabletcomputer, the computer system 500 of FIG. 5 may include one or moreantennas, radios, and other circuitry for communicating over wirelesssignals, such as for example communication using Wi-Fi, cellular, orother wireless signals.

As noted above, many websites utilize webpage analytics tools, tocapture metrics regarding their user traffic. To do so, web content suchas tags, scripts, and the like may be inserted into the webpage code.This causes a client accessing the webpage to send requests to theanalytics service, which are then tracked by the analytics service forpurposes of compiling reports.

While webpage analytics can offer useful information to a websiteoperator, use of webpage analytics is also not without cost. Indeed, theadditional requests sent by the client to the analytics servicenecessarily requires additional time and resources to perform, whichcould also increase the page load time of the webpage. To date, however,a “one size fits all” approach is usually taken with respect to webpageanalytics whereby the analytics tags, scrips, etc. are manually insertedinto the webpage code and always enabled.

Dynamic Web Content Management System

The techniques introduced herein allow for the dynamic management of webcontent, such as those inserted into webpage code for purposes ofanalytics. In some aspects, an agent may intercept webpage code beingsent to a client and dynamically decide to disable the tags, scripts, orthe like, inserted into the webpage code, based on any number offactors. For instance, in some embodiments, the web content for thewebpage analytics may be disabled dynamically based on factors such asperformance metrics associated with the website (e.g., page load times,traffic loads, etc.), the locations of the clients, security riskfactors, combinations thereof, or the like.

Illustratively, the techniques described herein may be performed byhardware, software, and/or firmware, such as in accordance with theillustrative application monitoring process 248, which may includecomputer executable instructions executed by the processor 220 toperform functions relating to the techniques described herein, e.g., inconjunction with corresponding processes of other devices in thecomputer network as described herein (e.g., on network agents,controllers, computing devices, servers, etc.).

Specifically, according to various embodiments, an agent executed by adevice intercepts webpage code for a website sent from an applicationserver to a client of the website. The agent identifies a portion of thewebpage code as being used for webpage analytics. The agent formsmodified webpage code by disabling the portion of the webpage code,based on one or more performance metrics associated with the website.The agent sends the modified webpage code to the client of the website.

Operationally, FIGS. 6A-6B illustrate an example architecture 600 fordynamic web content management, according to various embodiments. Asshown in FIG. 6A, consider the case in which a client 602 (e.g., aclient 405, a mobile device 415, etc.) sends a webpage request 606 to anapplication server 604 configured as a webserver for a website. Forinstance, webpage request 606 may be sent to a specific uniform resourceindicator (URI) or uniform resource locator (URL) that resolves to acertain IP address associated with application server 604, requestingaccess to a specific webpage of the website.

As would be appreciated, various exchanges may be performed betweenclient 602 and application server, in conjunction with webpage request606. For instance, if HTTP Secure (HTTPS) is used, client 602 andapplication server 604 may also perform a cryptographic exchange, suchas in accordance with the Transport Layer Security (TLS) protocol or thelike, to secure the communications sent between client 602 andapplication server 604.

In addition, in some embodiments, an authentication exchange may alsotake place between client 602 and application server 604. For instance,the webpage being requested by webpage request 606 may be protected andonly accessible to authorized users. In such cases, the user of client602 may also log into their account with the website served byapplication server 604. This login process may entail simply providing arecognized username and password to application server 604. In morecomplex scenarios, the login process may entail multifactorauthentication (MFA) or continuous MFA (cMFA), such as by requiring theuser of client 602 to provide biometric data, a verification code sentvia text, phone, email or the like, and/or other information that can beused to prove the identity of the user to application server 604.

According to various embodiments, as shown in FIG. 6B, the techniquesherein propose the use of an agent 610 (e.g., any of agents 310, 434,444, 454, 464, etc.) that is configured to intercept the webpage code612 returned by the web application 608 of application server 604 inresponse to a webpage request. For instance, as shown, web application608 may send webpage code 612 towards client 602, in response toreceiving the webpage request 606 sent by client 602 in FIG. 6A.

In various embodiments, agent 610 may be executed directly onapplication server 604, thereby performing the interception of agent610, locally. However, in further embodiments, agent 610 may also beimplemented as a cloud access security broker (CASB), as a sidecar proxy(e.g., a Kubernetes sidecar/Envoy proxy), on an intermediate devicebetween application server 604 and client 602, or the like.

A key function of agent 610 is to modify webpage code 612, as needed andin accordance with a defined policy, in various embodiments. In turn,agent 610 may send the modified webpage code 612 a to the client thatsent the webpage request, such as client 602. Such a policy may be setby default and/or specified via a user interface with agent 610,configuration file, or the like. Example factors considered by thepolicy for purposes of determining whether to modify webpage code 612may include, but are not limited to, any or all of the following:

-   -   One or more performance metrics associated with the website—for        instance, such metrics may include page load times, traffic load        metrics, or the like.    -   Whether the webpage request was sent by a bot—for instance,        agent 610 may opt to disable a portion of webpage code 612 when        client 602 is a bot or vice-versa.    -   Whether the requesting client was logged into an account        associated with the website    -   The identity of the user—for instance, agent 610 may opt to        disable a portion of webpage code 612 for a certain subset of        users.    -   The location of the client—for instance, agent 610 may estimate        the geolocation of client 602 based on its IP address or other        information and use this information to determine whether to        modify webpage code 612.    -   Whether the content poses a security risk—for instance, agent        610 may assess webpage code 612 to determine whether the content        poses a risk to disclosing sensitive data, presents a potential        vulnerability, or the like.    -   Etc.

In some embodiments, agent 610 may leverage machine learning, todetermine whether to modify webpage code 612 or not, based on any or allof the above factors (e.g., by estimating or forecasting certaininformation). Example machine learning techniques that agent 610 canemploy may include, but are not limited to, nearest neighbor (NN)techniques (e.g., k-NN models, replicator NN models, etc.), statisticaltechniques (e.g., Bayesian networks, etc.), clustering techniques (e.g.,k-means, mean-shift, etc.), neural networks (e.g., reservoir networks,artificial neural networks, etc.), support vector machines (SVMs),generative adversarial networks (GANs), long short-term memory (LSTM),logistic or other regression, Markov models or chains, principalcomponent analysis (PCA) (e.g., for linear models), singular valuedecomposition (SVD), multi-layer perceptron (MLP) artificial neuralnetworks (ANNs) (e.g., for non-linear models), replicating reservoirnetworks (e.g., for non-linear models, typically for timeseries), randomforest classification, or the like

According to various embodiments, agent 610 may modify webpage code 612to form modified webpage code 612 a by disabling at least a portionwebpage code 612, such as a portion that is used for website analytics.Such detection and modification may depend on the type of contentincluded in webpage code 612 for purposes of the analytics. Forinstance, agent 610 may assess webpage code 612 to identify web metadatatags, script tags, or the like.

In the case of web page metadata tags, webpage code 612 may include aHyperText Markup Language (HTML) meta tag elements of the form “<meta>,”which are often included in the <head> element of the webpage code.Generally, metadata is the data that describes the underlying data andthe <meta> element in HTML can be used to signify such information. Forinstance, webpage code 612 may include a metadata tag similar to thefollowing:

<!DOCTYPE html>  <html>   <head>    <meta charset=″utf-8″>    <metaname=″Description″ CONTENT=″Author: A.N. Author, Illustrator: P.Picture, Category: Books, Price: ??9.24, Length: 784 pages″>    <metaname=″google-site-verification″content=″+nxGUDJ4QpAZ519Bsjdi102tLVC21AIh5d1N123908vVuFHs34=″/>   <title>Example Books - high-quality used books for children</title>   <meta name=″robots″ content=″noindex,nofollow″>   </head> </html>

Such metadata tags are often used by search engines and can be abused bymalicious entities to trick users into going to sites that mimic that ofa legitimate website. In addition, these types of tags can also exposesensitive information to bots, search engines, and even to hackers.Thus, the use of metadata tags in webpage code 612 may be audited,regulated, and/or selectively allowed by agent 610. In such cases, agent610 may modify webpage code 612 to form modified webpage code 612 a fordelivery to client 602 by removing any portions thereof that includemetadata tags (e.g., those identified by agent 610 that are used foranalytics or other purposes).

In further embodiments, agent 610 may modify webpage code 612 to formmodified webpage code 612 a by identifying and modifying any portions ofwebpage code 612 that include scripts (e.g., those used for purposes ofwebpage analytics). For instance, agent 610 may identify a portion ofwebpage code 612 that include a Javascript or other script through itsinclusion of a <script> HTML element. For instance, a script associatedwith Google Analytics may look similar to the following:

<!-- Google Analytics -->  <script>  (function(i,s,o,g,r,a,m){i[′GoogleAnalyticsObject′]=r;i[r]=i[r]||function(){ (i[r].q=i[r].q||[ ]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)})(window,document,′script′,′https://www.google-analytics.com/analytics.js′,′ga′);   ga(′create′, ′UA-XXXXX-Y′, ′auto′);    ga(′send′, ′pageview′); </script> <!-- End Google Analytics -->

In such cases, agent 610 may modify webpage code 612 to remove the<script> tag and associated code, to completely disable the script andform modified webpage code 612 a, in some embodiments.

In further embodiments, agent 610 may disable a script in webpage code612 by simply disabling its synchronous operation. As would beappreciated, synchronous execution of a script can disrupt the renderingof the webpage by client 602, thereby increasing its page load time.Thus, rather than completely preventing execution of the script at all,agent 610 may instead opt to convert the script into asynchronous formin modified webpage code 612 a. For instance, agent 610 may insert an“async” attribute into the script, such as in the following example:

-   -   <script async        src=“https://www.google-analytics.com/analytics.js”></script>

Of course, agent 610 may always opt to leave existing web content inwebpage code 612, in accordance with its policy. For instance, if thenetwork traffic load is considered low and the page load times of thewebsite are acceptable, agent 610 may instead opt to send webpage code612 to client 602 without modification. In other embodiments, agent 610may be responsible for inserting the web content into webpage code 612,prior to delivery to client 602.

In conclusion, the techniques herein introduce a web content managementsystem that is able to make decisions on the fly based on a policy. Sucha policy may be set so as to allow or block web content based onconsiderations such as performance, security, and/or other runtimemetrics.

In closing, FIG. 7 illustrates an example simplified procedure fordynamic web content management, in accordance with one or moreembodiments described herein. For example, a non-generic, specificallyconfigured device (e.g., device 200) may perform procedure 2000 byexecuting stored instructions (e.g., illustrative application monitoringprocess 248). The procedure 700 may start at step 705, and continues tostep 710, where, as described in greater detail above, an agent executedby the device may intercept webpage code for a website sent from anapplication server to a client of the website. In various embodiments,the agent may comprise a sidecar proxy, cloud access security broker(CASB), or may even be executed directly on the web application serverthat serves the webpage to the client.

At step 715, as detailed above, the agent may identify a portion of thewebpage code as being used for webpage analytics. In some embodiments,the agent may do so by identifying a HyperText Markup Language (HTML)script tag in the portion of the webpage code. In further embodiments,the agent may do so by identifying an HTML metadata tag in the portionof the webpage code.

At step 720, the agent may form modified webpage code by disabling theportion of the webpage code, based on one or more performance metricsassociated with the website, as described in greater detail above. Invarious embodiment, the one or more performance metrics may comprise apage load time, a network traffic load, or the like. In someembodiments, the agent may disable the portion of the webpage code byremoving an HTML script tag from the webpage code. In furtherembodiments, the agent may disable immediate execution of a script inthe portion of the webpage code by converting the script into anasynchronous script. In some embodiments, the agent may also form themodified webpage code based further in part on a location of the client,whether a user of the client is logged into an account associated withthe website, or the like.

At step 725, as detailed above, the agent may send the modified webpagecode to the client of the website. Since the portion of the webpage codehas been disabled (e.g., by completely disabling the analytics contentinserted into the code or causing it to be executed asynchronously),this can help to improve performance and address any other concernsassociated with the webpage analytics. Of course, this process may alsobe performed dynamically, such as by allowing or enabling the analyticscontent to be sent to clients under certain conditions. Procedure 700then ends at step 730.

It should be noted that while certain steps within procedure 700 may beoptional as described above, the steps shown in FIG. 7 are merelyexamples for illustration, and certain other steps may be included orexcluded as desired. Further, while a particular order of the steps isshown, this ordering is merely illustrative, and any suitablearrangement of the steps may be utilized without departing from thescope of the embodiments herein.

While there have been shown and described illustrative embodimentsabove, it is to be understood that various other adaptations andmodifications may be made within the scope of the embodiments herein.For example, while certain embodiments are described herein with respectto certain types of networks in particular, the techniques are notlimited as such and may be used with any computer network, generally, inother embodiments. Moreover, while specific technologies, protocols, andassociated devices have been shown, such as Java, TCP, IP, and so on,other suitable technologies, protocols, and associated devices may beused in accordance with the techniques described above. For example,while certain terms have been used herein, such as tiers and nodes,other protocols may use other terms while still remaining within thescope of the present disclosure, such as process groups (instead oftiers), split process groups due to host grouping (instead of tiers withlonger names, such as “EAST-tomcat-server”), and so on. In addition,while certain devices are shown, and with certain functionality beingperformed on certain devices, other suitable devices and processlocations may be used, accordingly. That is, the embodiments have beenshown and described herein with relation to specific networkconfigurations (orientations, topologies, protocols, terminology,processing locations, etc.). However, the embodiments in their broadersense are not as limited, and may, in fact, be used with other types ofnetworks, protocols, and configurations.

Moreover, while the present disclosure contains many other specifics,these should not be construed as limitations on the scope of anyembodiment or of what may be claimed, but rather as descriptions offeatures that may be specific to particular embodiments of particularembodiments. Certain features that are described in this document in thecontext of separate embodiments can also be implemented in combinationin a single embodiment. Conversely, various features that are describedin the context of a single embodiment can also be implemented inmultiple embodiments separately or in any suitable sub-combination.Further, although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

For instance, while certain aspects of the present disclosure aredescribed in terms of being performed “by a server” or “by acontroller,” those skilled in the art will appreciate that agents of theapplication intelligence platform (e.g., application agents, networkagents, language agents, etc.) may be considered to be extensions of theserver (or controller) operation, and as such, any process stepperformed “by a server” need not be limited to local processing on aspecific server device, unless otherwise specifically noted as such.Furthermore, while certain aspects are described as being performed “byan agent” or by particular types of agents (e.g., application agents,network agents, etc.), the techniques may be generally applied to anysuitable software/hardware configuration (libraries, modules, etc.) aspart of an apparatus or otherwise.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. Moreover, the separation of various system components in theembodiments described in the present disclosure should not be understoodas requiring such separation in all embodiments.

The foregoing description has been directed to specific embodiments. Itwill be apparent, however, that other variations and modifications maybe made to the described embodiments, with the attainment of some or allof their advantages. For instance, it is expressly contemplated that thecomponents and/or elements described herein can be implemented assoftware being stored on a tangible (non-transitory) computer-readablemedium (e.g., disks/CDs/RAM/EEPROM/etc.) having program instructionsexecuting on a computer, hardware, firmware, or a combination thereof.Accordingly, this description is to be taken only by way of example andnot to otherwise limit the scope of the embodiments herein. Therefore,it is the object of the appended claims to cover all such variations andmodifications as come within the true intent and scope of theembodiments herein.

1. A method comprising: intercepting, by an agent executed by a device,webpage code for a website sent from an application server to a clientof the website; identifying, by the agent, a portion of the webpage codeas being used for webpage analytics by identifying a HyperText MarkupLanguage metadata tag in the portion of the webpage code for use by asearch engine; forming, by the agent, modified webpage code by disablingthe portion of the webpage code, based on one or more performancemetrics associated with the website, wherein the agent disables theportion of the webpage code by removing the HyperText Markup Languagemetadata tag from the webpage code; and sending, by the agent, themodified webpage code to the client of the website.
 2. The method as inclaim 1, wherein the one or more performance metrics comprise a pageload time.
 3. The method as in claim 1, wherein identifying the portionof the webpage code as being used for webpage analytics comprises:identifying a HyperText Markup Language script tag in the portion of thewebpage code.
 4. The method as in claim 3, wherein forming the modifiedwebpage code by disabling the portion of the webpage code comprises:removing the HyperText Markup Language script tag from the webpage code.5. The method as in claim 3, wherein forming the modified webpage codeby disabling the portion of the webpage code comprises: disablingimmediate execution of a script in the portion of the webpage code byconverting the script into an asynchronous script. 6-7. (canceled) 8.The method as in claim 1, wherein the one or more performance metricscomprise a network traffic load.
 9. (canceled)
 10. The method as inclaim 1, wherein the agent comprises a sidecar proxy or cloud accesssecurity broker.
 11. An apparatus, comprising: one or more networkinterfaces; a processor coupled to the one or more network interfacesand configured to execute one or more processes; and a memory configuredto store a process that is executable by the processor, the process whenexecuted configured to: intercept webpage code for a website sent froman application server to a client of the website; identify a portion ofthe webpage code as being used for webpage analytics by identifying aHyperText Markup Language metadata tag in the portion of the webpagecode for use by a search engine; form modified webpage code by disablingthe portion of the webpage code, based on one or more performancemetrics associated with the website, wherein the apparatus disables theportion of the webpage code by removing the HyperText Markup Languagemetadata tag from the webpage code; and send the modified webpage codeto the client of the website.
 12. The apparatus as in claim 11, whereinthe one or more performance metrics comprise a page load time.
 13. Theapparatus as in claim 11, wherein the apparatus identifies the portionof the webpage code as being used for webpage analytics by: identifyinga HyperText Markup Language script tag in the portion of the webpagecode.
 14. The apparatus as in claim 13, wherein the apparatus forms themodified webpage code by disabling the portion of the webpage code by:removing the HyperText Markup Language script tag from the webpage code.15. The apparatus as in claim 13, wherein the apparatus forms themodified webpage code by disabling the portion of the webpage code by:disabling immediate execution of a script in the portion of the webpagecode by converting the script into an asynchronous script. 16-17.(canceled)
 18. The apparatus as in claim 11, wherein the one or moreperformance metrics comprise a network traffic load.
 19. (canceled) 20.A tangible, non-transitory, computer-readable medium storing programinstructions that cause an agent of a device to execute a processcomprising: intercepting webpage code for a website sent from anapplication server to a client of the website; identifying a portion ofthe webpage code as being used for webpage analytics by identifying aHyperText Markup Language metadata tag in the portion of the webpagecode for use by a search engine; forming modified webpage code bydisabling the portion of the webpage code, based on one or moreperformance metrics associated with the website, wherein the agentdisables the portion of the webpage code by removing the HyperTextMarkup Language metadata tag from the webpage code; and sending themodified webpage code to the client of the website.